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Solar forecasting by K-Nearest Neighbors method with weather classification and physical model

机译:利用天气分类和物理模型的K最近邻法进行太阳预报

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With the increasing penetration of solar photovoltaic (PV) generation in the power system, the reliability of the distribution system and efficiency of PV systems have garnered increasing attention in recent years. Forecasting the PV output is one way to decrease the uncertainty of such power systems. In this study, we present a K-Nearest Neighbors algorithm based forecasting model, which can provide the estimated PV output by utilizing numerical weather and solar irradiance prediction data. This forecasting model also includes a weather condition classification process and a physical model of PV units. Numerical results are evaluated by using data from an existing 128kW rooftop PV system.
机译:随着太阳能光伏(PV)发电在电力系统中的渗透率不断提高,配电系统的可靠性和光伏系统的效率近年来受到越来越多的关注。预测光伏输出是减少此类电力系统不确定性的一种方法。在这项研究中,我们提出了一种基于K最近邻算法的预测模型,该模型可以通过利用数值天气和太阳辐照度预测数据来提供估计的PV输出。该预测模型还包括天气状况分类过程和PV单位的物理模型。通过使用现有128kW屋顶光伏系统的数据评估数值结果。

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